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The evaluation of the results from a fibre comparison given activity level propositions is well established when considering only a single group of potential primary transfers. However, secondary transfers are less prevalent in the literature despite their potential value, especially in cases where the primary transfers are not sufficiently informative. In particular, one can consider the fibres from frequented environments of the person of interest (POI) identified in a struggle. If the POI did struggle with the complainant, these fibres can potentially be recovered in small quantities on the surface of the complainant as a result of secondary or higher order transfers. Therefore, these fibres may provide useful information that can resolve competing propositions involving struggles, as well as forensic intelligence in the form of linkages or investigative leads. If a non-differentiation is indeed found between recovered fibres and fibres from the frequented environments of the POI, these results need to be properly interpreted. In this paper, a model, based on an object oriented Bayesian network (OOBN), for evaluating such findings along with its implementation is proposed. Using available data from the literature and other sources, the model was then used to assess a few hypothetical scenarios involving secondary transfers. The results provided useful insights into secondary transfer that help to validate the model and demonstrate the potential utility that can be gained by considering transfers beyond the primary order. Moreover, these results can be used to help guide future research by identifying gaps in the literature. Finally, the direct application to a case study was conducted to demonstrate the practical aspects of such a model., Competing Interests: Declaration of Competing Interest None, (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Generalised Bayes' factors and associated Bayesian networks are developed for the transfer of extrinsic evidence at the activity level, developments that extend previous work on activity level evaluation. A strategy for the assessment of extrinsic evidence is developed in stages with progressive increases in complexity. The final development is illustrated with an example involving fibres from clothing. This provides a list of factors involved in the consideration of a transfer case with activity level propositions and their roles in the determination of evidential value., Competing Interests: Declaration of Competing Interest None., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Dynamic signatures are recordings of signatures made on digitizing devices such as tablet PCs. These handwritten signatures contain both dynamic and spatial information on every data point collected during the signature movement and can therefore be described in the form of multivariate data. The management of dynamic signatures represents a challenge for the forensic science community through its novelty and the volume of data available. Much as for static signatures, the authenticity of dynamic signatures may be doubted, which leads to a forensic examination of the unknown source signature. The Bayes' factor, as measure of evidential support, can be assigned with statistical models to discriminate between competing propositions. In this respect, the limitations of existing probabilistic solutions to deal with dynamic signature evidence is pointed out and explained in detail. In particular, the necessity to remove the independence assumption between questioned and reference material is emphasized., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

In forensic science it is not rare that common sayings are used to support particular inferences. A typical example is the adage 'The absence of evidence is not evidence of absence'. This paper analyzes the rationale hidden behind such statement and it offers a structural way to approach the analysis of this particular adage throughout a careful analysis of four different scenarios., (Copyright © 2019 Elsevier B.V. All rights reserved.)

This article focuses on dynamic signatures and their features. It provides a detailed and critical review of dynamic feature variations and circumstantial parameters affecting dynamic signatures. The state of the art summarizes available knowledge, meant to assist the forensic practitioner in cases presenting extraordinary writing conditions. The studied parameters include hardware-related issues, aging and the influence of time, as well as physical and mental states of the writer. Some parameters, such as drug and alcohol abuse or medication, have very strong effects on handwriting and signature dynamics. Other conditions such as the writer's posture and fatigue have been found to affect feature variation less severely. The need for further research about the influence of these parameters, as well as handwriting dynamics in general is highlighted. These factors are relevant to the examiner in the assessment of the probative value of the reported features. Additionally, methodology for forensic examination of dynamic signatures is discussed. Available methodology and procedures are reviewed, while pointing out major technical and methodological advances in the field of forensic handwriting examination. The need for sharing the best practice manuals, standard operating procedures and methodologies to favor further progress is accentuated., (Copyright © 2018 Elsevier B.V. All rights reserved.)

In this paper we critically discuss the definition and use of cut-off values by forensic scientists, for example in forensic toxicology, and point out when and why such values - and ensuing categorical conclusions - are inappropriate concepts for helping recipients of expert information with their questions of interest. Broadly speaking, a cut-off is a particular value of results of analyses of a target substance (e.g., a toxic substance or one of its metabolites in biological sample from a person of interest), defined in a way such as to enable scientists to suggest conclusions regarding the condition of the person of interest. The extent to which cut-offs can be reliably defined and used is not unanimously agreed within the forensic science community, though many practitioners - especially in operational laboratories - rely on cut-offs for reasons such as ease of use and simplicity. In our analysis, we challenge this practice by arguing that choices made for convenience should not be to the detriment of balance and coherence. To illustrate our discussion, we will choose the example of alcohol markers in hair, used widely by forensic toxicologists to reach conclusions regarding the drinking behaviour of individuals. Using real data from one of the co-authors' own work and recommendations of cut-offs published by relevant professional organisations, we will point out in what sense cut-offs are incompatible with current evaluative guidelines (e.g., [31]) and show how to proceed logically without cut-offs by using a standard measure for evidential value. Our conclusions run counter to much current practice, but are inevitable given the inherent definitional and conceptual shortcomings of scientific cut-offs. We will also point out the difference between scientific cut-offs and legal thresholds and argue that the latter - but not the former - are justifiable and can be dealt with in logical evaluative procedures., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Forensic age estimation, a branch of forensic science, has received renewed attention lately mainly due to societal migration phenomena. And yet, the interpretation of age-related evidence is still largely neglected as a field, the literature being usually limited to technical discussions strictly pertaining to the statistical methodologies to be used in estimation process. This short communication aims to highlight the fundamental role of evidence evaluation and interpretation in forensic age estimation. We illustrate why the Bayesian approach represents the best choice in such a perspective., (Copyright © 2017 Elsevier B.V. All rights reserved.)

This paper reports on a study to assess the potential of measurements of magnetism, using a proprietary magnetic analysis system, for the routine analysis of toners on documents printed by black and white electrophotographic systems. Magnetic properties of black toners on documents printed by a number of different devices were measured and compared. Our results indicate that the analysis of magnetism is complementary to traditional methods for analysing black toners, such as FTIR. Further, we find that the analysis of magnetism is realistically applicable in closed set cases, that is when the number of potential printing devices can be clearly defined., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Analysis of marks recovered from different crime scenes can be useful to detect a linkage between criminal cases, even though a putative source for the recovered traces is not available. This particular circumstance is often encountered in the early stage of investigations and thus, the evaluation of evidence association may provide useful information for the investigators. This association is evaluated here from a probabilistic point of view: a likelihood ratio based approach is suggested in order to quantify the strength of the evidence of trace association in the light of two mutually exclusive propositions, namely that the n traces come from a common source or from an unspecified number of sources. To deal with this kind of problem, probabilistic graphical models are used, in form of Bayesian networks and object-oriented Bayesian networks, allowing users to intuitively handle with uncertainty related to the inferential problem., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Throughout forensic science and adjacent branches, academic researchers and practitioners continue to diverge in their perception and understanding of the notion of 'individualization', that is the claim to reduce a pool of potential donors of a forensic trace to a single source. In particular, recent shifts to refer to the practice of individualization as a decision have been revealed as being a mere change of label [1], leaving fundamental changes in thought and understanding still pending. What is more, professional associations and practitioners shy away from embracing the notion of decision in terms of the formal theory of decision in which individualization may be framed, mainly because of difficulties to deal with the measurement of desirability or undesirability of the consequences of decisions (e.g., using utility functions). Building on existing research in the area, this paper presents and discusses fundamental concepts of utilities and losses with particular reference to their application to forensic individualization. The paper emphasizes that a proper appreciation of decision tools not only reduces the number of individual assignments that the application of decision theory requires, but also shows how such assignments can be meaningfully related to constituting features of the real-world decision problem to which the theory is applied. It is argued that the decisonalization of individualization requires such fundamental insight to initiate changes in the fields' underlying understandings, not merely in their label., (Copyright © 2016 The Author(s). Published by Elsevier Ireland Ltd.. All rights reserved.)

Many people regard the concept of hypothesis testing as fundamental to inferential statistics. Various schools of thought, in particular frequentist and Bayesian, have promoted radically different solutions for taking a decision about the plausibility of competing hypotheses. Comprehensive philosophical comparisons about their advantages and drawbacks are widely available and continue to span over large debates in the literature. More recently, controversial discussion was initiated by an editorial decision of a scientific journal [1] to refuse any paper submitted for publication containing null hypothesis testing procedures. Since the large majority of papers published in forensic journals propose the evaluation of statistical evidence based on the so called p-values, it is of interest to expose the discussion of this journal's decision within the forensic science community. This paper aims to provide forensic science researchers with a primer on the main concepts and their implications for making informed methodological choices., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

In the past few decades, the rise of criminal, civil and asylum cases involving young people lacking valid identification documents has generated an increase in the demand of age estimation. The chronological age or the probability that an individual is older or younger than a given age threshold are generally estimated by means of some statistical methods based on observations performed on specific physical attributes. Among these statistical methods, those developed in the Bayesian framework allow users to provide coherent and transparent assignments which fulfill forensic and medico-legal purposes. The application of the Bayesian approach is facilitated by using probabilistic graphical tools, such as Bayesian networks. The aim of this work is to test the performances of the Bayesian network for age estimation recently presented in scientific literature in classifying individuals as older or younger than 18 years of age. For these exploratory analyses, a sample related to the ossification status of the medial clavicular epiphysis available in scientific literature was used. Results obtained in the classification are promising: in the criminal context, the Bayesian network achieved, on the average, a rate of correct classifications of approximatively 97%, whilst in the civil context, the rate is, on the average, close to the 88%. These results encourage the continuation of the development and the testing of the method in order to support its practical application in casework., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

This study presents a classification criteria for two-class Cannabis seedlings. As the cultivation of drug type cannabis is forbidden in Switzerland, law enforcement authorities regularly ask laboratories to determine cannabis plant's chemotype from seized material in order to ascertain that the plantation is legal or not. In this study, the classification analysis is based on data obtained from the relative proportion of three major leaf compounds measured by gas-chromatography interfaced with mass spectrometry (GC-MS). The aim is to discriminate between drug type (illegal) and fiber type (legal) cannabis at an early stage of the growth. A Bayesian procedure is proposed: a Bayes factor is computed and classification is performed on the basis of the decision maker specifications (i.e. prior probability distributions on cannabis type and consequences of classification measured by losses). Classification rates are computed with two statistical models and results are compared. Sensitivity analysis is then performed to analyze the robustness of classification criteria., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

This paper extends previous research on the use of multivariate continuous data in comparative handwriting examinations, notably for gender classification. A database has been constructed by analyzing the contour shape of loop characters of type a and d by means of Fourier analysis, which allows characters to be described in a global way by a set of variables (e.g., Fourier descriptors). Sample handwritings were collected from right- and left-handed female and male writers. The results reported in this paper provide further arguments in support of the view that investigative settings in forensic science represent an area of application for which the Bayesian approach offers a logical framework. In particular, the Bayes factor is computed for settings that focus on inference of gender and handedness of the author of an incriminated handwritten text. An emphasis is placed on comparing the efficiency for investigative purposes of characters a and d., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

This paper reports on the purpose, design, methodology and target audience of E-learning courses in forensic interpretation offered by the authors since 2010, including practical experiences made throughout the implementation period of this project. This initiative was motivated by the fact that reporting results of forensic examinations in a logically correct and scientifically rigorous way is a daily challenge for any forensic practitioner. Indeed, interpretation of raw data and communication of findings in both written and oral statements are topics where knowledge and applied skills are needed. Although most forensic scientists hold educational records in traditional sciences, only few actually followed full courses that focussed on interpretation issues. Such courses should include foundational principles and methodology - including elements of forensic statistics - for the evaluation of forensic data in a way that is tailored to meet the needs of the criminal justice system. In order to help bridge this gap, the authors' initiative seeks to offer educational opportunities that allow practitioners to acquire knowledge and competence in the current approaches to the evaluation and interpretation of forensic findings. These cover, among other aspects, probabilistic reasoning (including Bayesian networks and other methods of forensic statistics, tools and software), case pre-assessment, skills in the oral and written communication of uncertainty, and the development of independence and self-confidence to solve practical inference problems. E-learning was chosen as a general format because it helps to form a trans-institutional online-community of practitioners from varying forensic disciplines and workfield experience such as reporting officers, (chief) scientists, forensic coordinators, but also lawyers who all can interact directly from their personal workplaces without consideration of distances, travel expenses or time schedules. In the authors' experience, the proposed learning initiative supports participants in developing their expertise and skills in forensic interpretation, but also offers an opportunity for the associated institutions and the forensic community to reinforce the development of a harmonized view with regard to interpretation across forensic disciplines, laboratories and judicial systems., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)

A recent publication in this journal [1] presented the results of a field study that revealed the data provided by the fingermarks not processed in a forensic science laboratory. In their study, the authors were interested in the usefulness of this additional data in order to determine whether such fingermarks would have been worth submitting to the fingermark processing workflow. Taking these ideas as a starting point, this communication here places the fingermark in its context of a case brought before a court, and examines the question of processing or not processing a fingermark from a decision-theoretic point of view. The decision-theoretic framework presented provides an answer to this question in the form of a quantified expression of the expected value of information (EVOI) associated with the processed fingermark, which can then be compared with the cost of processing the mark., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

Sampling issues represent a topic of ongoing interest to the forensic science community essentially because of their crucial role in laboratory planning and working protocols. For this purpose, forensic literature described thorough (bayesian) probabilistic sampling approaches. These are now widely implemented in practice. They allow, for instance, to obtain probability statements that parameters of interest (e.g., the proportion of a seizure of items that present particular features, such as an illegal substance) satisfy particular criteria (e.g., a threshold or an otherwise limiting value). Currently, there are many approaches that allow one to derive probability statements relating to a population proportion, but questions on how a forensic decision maker--typically a client of a forensic examination or a scientist acting on behalf of a client--ought actually to decide about a proportion or a sample size, remained largely unexplored to date. The research presented here intends to address methodology from decision theory that may help to cope usefully with the wide range of sampling issues typically encountered in forensic science applications. The procedures explored in this paper enable scientists to address a variety of concepts such as the (net) value of sample information, the (expected) value of sample information or the (expected) decision loss. All of these aspects directly relate to questions that are regularly encountered in casework. Besides probability theory and bayesian inference, the proposed approach requires some additional elements from decision theory that may increase the efforts needed for practical implementation. In view of this challenge, the present paper will emphasise the merits of graphical modelling concepts, such as decision trees and bayesian decision networks. These can support forensic scientists in applying the methodology in practice. How this may be achieved is illustrated with several examples. The graphical devices invoked here also serve the purpose of supporting the discussion of the similarities, differences and complementary aspects of existing bayesian probabilistic sampling criteria and the decision-theoretic approach proposed throughout this paper., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)

This paper applies probability and decision theory in the graphical interface of an influence diagram to study the formal requirements of rationality which justify the individualization of a person found through a database search. The decision-theoretic part of the analysis studies the parameters that a rational decision maker would use to individualize the selected person. The modeling part (in the form of an influence diagram) clarifies the relationships between this decision and the ingredients that make up the database search problem, i.e., the results of the database search and the different pairs of propositions describing whether an individual is at the source of the crime stain. These analyses evaluate the desirability associated with the decision of 'individualizing' (and 'not individualizing'). They point out that this decision is a function of (i) the probability that the individual in question is, in fact, at the source of the crime stain (i.e., the state of nature), and (ii) the decision maker's preferences among the possible consequences of the decision (i.e., the decision maker's loss function). We discuss the relevance and argumentative implications of these insights with respect to recent comments in specialized literature, which suggest points of view that are opposed to the results of our study., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)

This paper focuses on likelihood ratio based evaluations of fibre evidence in cases in which there is uncertainty about whether or not the reference item available for analysis - that is, an item typically taken from the suspect or seized at his home - is the item actually worn at the time of the offence. A likelihood ratio approach is proposed that, for situations in which certain categorical assumptions can be made about additionally introduced parameters, converges to formula described in existing literature. The properties of the proposed likelihood ratio approach are analysed through sensitivity analyses and discussed with respect to possible argumentative implications that arise in practice., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)

This paper extends previous research and discussion on the use of multivariate continuous data, which are about to become more prevalent in forensic science. As an illustrative example, attention is drawn here on the area of comparative handwriting examinations. Multivariate continuous data can be obtained in this field by analysing the contour shape of loop characters through Fourier analysis. This methodology, based on existing research in this area, allows one describe in detail the morphology of character contours throughout a set of variables. This paper uses data collected from female and male writers to conduct a comparative analysis of likelihood ratio based evidence assessment procedures in both, evaluative and investigative proceedings. While the use of likelihood ratios in the former situation is now rather well established (typically, in order to discriminate between propositions of authorship of a given individual versus another, unknown individual), focus on the investigative setting still remains rather beyond considerations in practice. This paper seeks to highlight that investigative settings, too, can represent an area of application for which the likelihood ratio can offer a logical support. As an example, the inference of gender of the writer of an incriminated handwritten text is forwarded, analysed and discussed in this paper. The more general viewpoint according to which likelihood ratio analyses can be helpful for investigative proceedings is supported here through various simulations. These offer a characterisation of the robustness of the proposed likelihood ratio methodology., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)

This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)

Part I of this series of articles focused on the construction of graphical probabilistic inference procedures, at various levels of detail, for assessing the evidential value of gunshot residue (GSR) particle evidence. The proposed models--in the form of Bayesian networks--address the issues of background presence of GSR particles, analytical performance (i.e., the efficiency of evidence searching and analysis procedures) and contamination. The use and practical implementation of Bayesian networks for case pre-assessment is also discussed. This paper, Part II, concentrates on Bayesian parameter estimation. This topic complements Part I in that it offers means for producing estimates usable for the numerical specification of the proposed probabilistic graphical models. Bayesian estimation procedures are given a primary focus of attention because they allow the scientist to combine (his/her) prior knowledge about the problem of interest with newly acquired experimental data. The present paper also considers further topics such as the sensitivity of the likelihood ratio due to uncertainty in parameters and the study of likelihood ratio values obtained for members of particular populations (e.g., individuals with or without exposure to GSR)., (Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.)

This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software., (Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.)

As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches--with the help of Bayesian networks--for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

Well developed experimental procedures currently exist for retrieving and analyzing particle evidence from hands of individuals suspected of being associated with the discharge of a firearm. Although analytical approaches (e.g. automated Scanning Electron Microscopy with Energy Dispersive X-ray (SEM-EDS) microanalysis) allow the determination of the presence of elements typically found in gunshot residue (GSR) particles, such analyses provide no information about a given particle's actual source. Possible origins for which scientists may need to account for are a primary exposure to the discharge of a firearm or a secondary transfer due to a contaminated environment. In order to approach such sources of uncertainty in the context of evidential assessment, this paper studies the construction and practical implementation of graphical probability models (i.e. Bayesian networks). These can assist forensic scientists in making the issue tractable within a probabilistic perspective. The proposed models focus on likelihood ratio calculations at various levels of detail as well as case pre-assessment.

The field of forensic science has profited from recent advances in the elicitation of various kinds probabilistic data. These provide the basis for implementing probabilistic inference procedures (e.g., in terms of likelihood ratios) that address the task of discriminating among competing target propositions. There is ongoing discussion, however, whether forensic identification, that is, a conclusion that associates a potential source (such as an individual or object) with a given item of scientific evidence (e.g., a biological stain or a tool mark), can, if ever, be based on purely probabilistic argument. With regard to this issue, the present paper proposes to analyze the process of forensic identification from a decision theoretic point of view. Existing probabilistic inference procedures are used therein as an integral part. The idea underlying the proposed analyses is that inference and decision are connected in the sense that the former is the point of departure for the latter. As such the approach forms a coordinated whole, that is a framework also known in the context as 'full Bayesian (decision) approach'. This study points out that, as a logical extension to purely probabilistic reasoning, a decision theoretic conceptualization of forensic identification allows the content and structure of arguments to be examined from a reasonably distinct perspective and common fallacious interpretations to be avoided.

This paper discusses recommendations concerning the use of prior probabilities that underlie recent, but in no way novel, proposals of presenting scientific evidence in terms of posterior probabilities, in the context sometimes referred to as the 'full Bayes' approach'. A chief issue of this procedure is a proposal that--given the unavailability of case-specific circumstantial information--scientists should consider the prior probabilities of the propositions under which scientific evidence is evaluated as equal. The discussion presented here draws the reader's attention to the fact that the philosophical foundations of such a recommendation (in particular, attempted justifications through the Principle of Maximum Entropy (PME)) are far more controversial than what is actually admitted by the advocates for their use in the theory and practice of forensic science. Invoking only basic assumptions and the mathematical rules of probability calculus, the authors of this paper propose an argument that shows that there can be other more feasible and defensible strategies for eliciting reasonable prior probabilities. It is solely demanded that the reasoner is willing to make up his mind seriously on certain standard issues of fairly general criminal cases, such as evidential relevance or the probability of a suspect's guilt. However, because these issues intimately pertain to the responsibility of the trier of the fact, it is argued here that scientists' attempts to define appropriate prior probabilities should continue to be considered as untenable for the need.

In the practice of forensic handwriting experts, the size of the writing on a questioned document may be different from that of known samples. In this study, the hypothesis of shape invariance of handwritten closed loops across size increasing was tested. A Fourier methodology was applied to 2325 small letters (591 a loops, 547 d loops, 596 o loops and 591 q loops) and 692 enlarged letters (162 a loops, 173 d loops, 173 o loops and 184 q loops), in a population of 13 writers who were asked to write letters in their usual size and about three times larger. Most of the writers presented similar modifications when increasing the size of the loops; they produced enlarged loops significantly more round and less slanted towards the right or the left. Furthermore, a discrimination was demonstrated between the writers on the basis of the enlarged loops, with a correct classification rate superior to 90%, whatever the letter (a, d, o or q). A classification of the enlarged loops in their corresponding writer was then possible. On the contrary, when comparing the enlarged loops to the small ones, almost one half of the enlarged loops were allocated to a wrong writer. Shape invariance was thus not supported for this particular application. Consequently, when comparing documents with a different writing size, differences in loops shape should be interpreted cautiously because they may be due to a different writer, but they may also be due to an enlargement of the loops. Therefore, reference material of similar writing size to that of the questioned writing should be requested for the comparison of handwritten loops.

Currently, the use of isotopic ratio as corroborative evidence in criminal trials is explored. Beyond the analytical challenges that have been reported elsewhere, the crucial issue of the interpretation of analytical results in a fair and balanced way remains poorly documented. The aim of this paper is to propose a likelihood ratio approach for the evaluation of stable isotope data acquired from semtex samples. It will also lead to recommendations in relation to the acquisition of normalised international data.

A methodology based on Fourier descriptors that was previously validated has been applied to 13 writers in order to quantify the polymorphism degree of the shape of the loops of the handwritten characters a, d, o and q. In a first step, the discriminating power of the parameters extracted from these letters was investigated. The loop of the letter d appeared to be the most discriminant with a correct classification rate of 82.4%, whereas the least discriminant one was the loop of the letter o (69.7%). The second aim of the study was to extract grouping characteristics which make it possible to discriminate between writer sets, whatever the letter. Trends in the writing of loops could effectively be shown: the 13 writers of the study were separated into five main groups according to the shape and surface of their loops. The most discriminating features between the writer groups were the importance of the loops elongation and the surface of the loops. Finally, the differences between writers belonging to distinct groups could be characterized more precisely, and differences between writers belonging to the same group were revealed; the individual writings were distinguished by the variability of the parameters of shape and surface of their loops and the morphological distances between its different letters. The correct classification rates reached in this study suggest that carrying out an expertise of fragmentary samples of handwriting comprising only some loops is completely possible.

The present paper addresses issues that affect both the separate as well as the joint evaluation of firearm evidence (i.e., marks) and gunshot residues (GSR). Mark evidence will be used as a basis to discriminate among barrels through which a bullet in question might have been shot whereas GSR will be used to draw inferences about the distance of firing. Particular attention is drawn to the coherent handling of uncertainties associated with the various parameters considered within each item of evidence. The proposed analysis relies on a probabilistic viewpoint that uses graphical models (i.e., Bayesian networks) as an aid to cope with the complexity induced by the number of variables considered. The paper discusses how an approach based on a probabilistic network environment can be used for the formal analysis and construction of arguments. Emphasis is made on the gain of insight into structural dependencies that may be uncovered when the evaluative process is extended beyond single items of scientific evidence.

Bayesian networks (BNs) are a kind of graphical model that formally combines elements of graph and probability theory. BNs are a mathematically and statistically rigorous technique allowing their user to define a pictorial representation of assumed dependencies and influences among a set of variables deemed to be relevant for a particular inferential problem. The formalism allows one to process newly acquired evidence according to the rules of probability calculus. Applications of BNs have been reported in various forensic disciplines. However, there seems to be some reluctance to consider BNs as a more general framework for representing and evaluating sources of uncertainties associated with scientific evidence. Notably, BNs are widely thought of as an essentially numerical method, requiring "exact" numbers with a high "accuracy". The present paper aims to draw the reader's attention to the point that the availability of hard numerical data is not a necessary requirement for using BNs in forensic science. An abstraction of quantitative BNs, known as qualitative probabilistic networks (QPNs), and sensitivity analyses are presented and their potential applications discussed. As a main difference to their quantitative counterpart, QPNs contain qualitative probabilistic relationships instead of numerical relations. Sensitivity analyses consist of varying the probabilities assigned to one or more variables and evaluating the effect on one or more other variables of interest. Both QPNs and sensitivity analyses appear to be useful concepts that permit one to work in contexts with acute lack of numerical data and where reasoning consistent with the laws of probability should nevertheless be performed.

In view of contributing to the scientific validation of the individuality of handwriting, the testing of the two so called fundamental laws of handwriting--1: no two people write exactly alike; 2: no one person writes the same word exactly the same way twice--was approached by analysing the shape of 445 handwritten capital characters O produced by three individuals. A methodology based on classical Fourier descriptors was applied to the characters contours, which were extracted through an automated procedure of image analysis. Precise individual characterization of the shape was possible through Fourier analysis. Within-writer variability of the shape of character O for the writers selected could be shown in an objective and quantitative way through the statistical analysis of the Fourier descriptors. It was demonstrated that this polymorphism differed between the three writers. Differentiation between writers was quantitatively demonstrated by discriminant analysis of the Fourier descriptors, and by the existence of marked morphological distances between the set of characters O of each writer. The degree of dissimilitude of the character O writings could, thus, be assessed. Because of relatively reduced within-writer variability and a pronounced differentiation between the writers, a morphological profile could be established and discrimination between writers could be obtained through the quantification of the shape of one handwritten character.

This paper extends a previous discussion of the use of Bayesian networks for evaluating evidence in the forensic investigation of fire incidents. Bayesian networks are proposed for two casework examples and the practical implications studied in detail. Such networks were found to provide precious support in addressing some of the wide range of issues that affect the coherent evaluation of evidence.

The forensic investigation of the origin and cause of a fire incident is a particularly demanding area of expertise. As the available evidence is often incomplete or vague, uncertainty is a key element. The present study is an attempt to approach this through the use of Bayesian networks, which have been found useful in assisting human reasoning in a variety of disciplines in which uncertainty plays a central role. The present paper describes the construction of a Bayesian network (BN) and its use for drawing inferences about propositions of interest, based upon a single, possibly non replicable item of evidence: detected residual quantities of a flammable liquid in fire debris.

Bayesian networks (BNs) are mathematically and statistically rigorous techniques for handling uncertainty. The field of forensic science has recently attributed increased attention to the many advantages of this graphical method for assisting the evaluation of scientific evidence. However, the majority of contributions that relate to this topic restrict themselves to the presentation of already "constructed" BNs, and often, only a few explanations are given as to how one obtains a specific BN structure for a given problem. Based on several examples, the present paper will therefore attempt to explain in more detail some guiding considerations that might be helpful for the elicitation of appropriate structures for BNs.

Alleles and haplotypes frequencies for 10 Y-chromosome STR loci (DYS19, DYS385 I/II, DYS389I, DYS389II, DYS390, DYS391, DYS392, DYS393, DYS438 and DYS439), included in the Y-Plex6 and Y-Plex5 kits were determined for a Tunisian population sample of 100 male individuals.

To characterise links between different illicit drugs chemical profiles, various distance or correlation measurements are available.Different comparison methods have been tested and a method based on a correlation coefficient using a square cosine function was chosen to compare heroin chemical profiles. Its functioning and graphical representation are described. An assessment of the number of false positives is calculated and lead to a negligible number.Moreover, it emerges from the studies that possible variations in impurity peak areas subject to possible degradations do not influence the C correlation value nor question the already established links. This solid, reliable and simple method appears therefore suitable for heroin samples comparison, links profiling and routine use.

The evaluation of a link between two heroin seizures using a descriptive method is presented. It is based on the measure of the angles between two chromatograms assimilated to vectors, and interpreted using a continuous approach based on the likelihood ratio of Bayes' theorem. A complete evaluation model thus avoids the drawbacks of decision thresholds used until now to establish a link. Validation is obtained through tests and simulation methods.

A simplified method of the His bundle analysis is evaluated by the study of 110 forensic cases. The atrioventricular node or its part were observed in 96 cases (87.3%), penetrating bundle in 92 cases (83.6%), branching and left bundles branch in 109 cases (99.1%) and right bundle branch in 73 cases (66.4%). The changes such as fibrosis and fatty infiltration show statistically significant differences (P<0.01) between progressive age groups confirming their degenerative and age-related nature. The study included as well nine cases of sudden unexpected death and two cases of sudden infant death syndrome (SIDS), for which the autopsy with histological examination and toxicological analysis resulted negative. For nine of these cases, pathological lesions were found which can even explain the fatal issue. Moreover, in the cases with known cause of death, potentially lethal changes were noticed. This simple, low cost technique could be proposed to forensic pathologists as easy to fit into the routine processing of autopsy material, allowing the detection of major abnormalities with minimal effort. The authors also consider the difficulties related to the interpretation of the pathological findings in the conduction system.

Genotype and allele frequencies distribution for 15 PCR-based loci included in the Promega PowerPlex 16 kit were determined for a Tunisian population sample of 196 unrelated individuals.

Bayesian networks provide a valuable aid for representing epistemic relationships in a body of uncertain evidence. The paper proposes some simple Bayesian networks for standard analysis of patterns of inference concerning scientific evidence, with a discussion of the rationale behind the nets, the corresponding probabilistic formulas, and the required probability assessments.

Nandrolone (19-nortestosterone) is a widely used anabolic steroid in sports where strength plays an essential role. Once nandrolone has been metabolised, two major metabolites are excreted in urine, 19-norandrosterone (NA) and 19-noretiocholanolone (NE). In 1997, in France, quite a few sportsmen had concentrations of 19-norandrosterone very close to the IOC cut off limit (2ng/ml). At that time, a debate took place about the capability of the human male body to produce by itself these metabolites without any intake of nandrolone or related compounds. The International Football Federation (FIFA) was very concerned with this problematic, especially because the World Cup was about to start in France. In this respect, a statistical study was held with all football players from the first and second divisions of the Swiss Football National League. All players gave a urine sample after effort and around 6% of them showed traces of 19-norandrosterone. These results were compared with amateur football players (control group) and around 6% of them had very small amounts of 19-norandrosterone and/or 19-noretiocholanolone in urine after effort, whereas none of them had detectable traces of one or the other metabolite before effort. The origin of these compounds in urine after a strenuous physical activity is still unknown, but three hypotheses can be put forward. First, an endogenous production of nandrolone metabolites takes place. Second, nandrolone metabolites are released from the fatty tissues after an intake of nandrolone, some related compounds or some contaminated nutritive supplements. Finally, the sportsmen may have taken something during or just before the football game.

Forensic scientists working in 12 state or private laboratories participated in collaborative tests to improve the reliability of the presentation of DNA data at trial. These tests were motivated in response to the growing criticism of the power of DNA evidence. The experts' conclusions in the tests are presented and discussed in the context of the Bayesian approach to interpretation. The use of a Bayesian approach and subjective probabilities in trace evaluation permits, in an easy and intuitive manner, the integration into the decision procedure of any revision of the measure of uncertainty in the light of new information. Such an integration is especially useful with forensic evidence. Furthermore, we believe that this probabilistic model is a useful tool (a) to assist scientists in the assessment of the value of scientific evidence, (b) to help jurists in the interpretation of judicial facts and (c) to clarify the respective roles of scientists and of members of the court. Respondents to the survey were reluctant to apply this methodology in the assessment of DNA evidence.